PROMISE 2011: What Prediction Model Should Be?

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PROMISE 2011
"What Prediction Model Should Be?"
Qing Wang

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  • 1. Whatprediction model should be?
    Institute of Software Chinese Academy of Sciences
    Qing Wang
  • 2. Why we use prediction model?
    Understand the past behavious of process
    Control the present behavious of process
    Predict the future behavious of process
    2
  • 3. How to understand the past behavious?
    Based on the historical data which has been collected from relative processes
    Apply appropriate measure and analysis techniques to analyze the data quantitatively.
    Try to find some nature characteristics
    Is stable?Nature bounds?
    Does some quantitative relationship among process attributes?
    Can be stratified /segmented or composed further?
    3
  • 4. How to control the present behavious?
    Based on the nature bounds (baselines) to establish the desired objectives of project
    Compare the present data to say if it is compliant with the nature bounds.
    Take proper action to correct the deviation
    Monitor and evaluate the effect of correct action
    4
  • 5. How to predict the future behavious?
    Based on the quantitative relationship which established depend on the understanding of past behavious.
    Predict the interim outcome and final outcome of project to know if the project is going well toward the project objectives.
    5
  • 6. What is the essential ?
    Differ from estimation model
    Deterministic, uncertainty, ……
    Use past and present data to predict future
    Some dependent X factors, predict independent Y outcomes
    The measurement for Xs and Y make sense
    Data collection timely and frequently
    Dynamical
    Statistical, probability, simulation-based
    6
  • 7. Must be careful when establish prediction model?
    Use real world and relevant data
    Align the necessary project objectives
    SMART principle
    Specific
    Measurable
    Attainable
    Relevant
    Time-bound
    Cost-benefit balance
    Feedback and refinement
    7
  • 8. Practical Case – A CMMI ML4 organization
    Issue: the organization found there are more than 90% projects delay is due to test and fix bugs need much more time than estimated
    Question: How to predict the effort and schedule of test process?
    Method:
    Identify the factors which impact the effort and schedule of test process
    Establish a prediction model use these factors
    Measure and control these factors
    Predict the effort and schedule of test based on the factors when they were got
  • 9. The process
    Each user case has been implemented by requirement analyze, design and coding
    reviews for each user case for each development activity were conducted respectively and defect data was recorded
    Each iteration has a unique testing and data was recorded
    The subsystem of each iteration was delivered to customer as a intermediate result, they must be on schedule and have good quality
    System testing was conducted when all iterations were completed (each release)
  • 10. Process improvement objectives
    Goal
    G1: manage the schedule of each iteration and reduce the defect as soon as possible
    G2: manage the system test to detect and fix defects as many as possible
  • 11. G1: in each iteration
    All defect data related requirement analysis, design and coding were collected before testing
    Can we find some quantitative relationship between these data and the effort of testing process?
    There are two primary activities in testing process
    Detect defects
    Fix defects
  • 12. Get data from 16 history projects
  • 13. Defect injection analysis - 1
    13
    Defect injected in requirement analysis
    Defect injected in design
  • 14. Defect injection analysis - 2
    Defect injected in coding
    The factor can be control , it can be used to establish prediction model
    Y is the effort of fix defects.
    If the predicted effort beyond estimate, they should assign more engineers to assure on schedule deliver of each iteration.
  • 15. G2: for system testing
  • 16. Use controllable factor to predict
    16
    Similar prediction model for system testing can be established.
    The possible impact factors could be:
    The defects injected in requirement, design and coding
    The defects removed respectively
    The defects removed in integrated testing of each iteration
    ……
  • 17. Summary
    17
    All data can be get
    The factors which used to establish prediction model are controllable and independent
    Statistical techniques are used to do analysis
    Prediction object is relevant to the organization process improvement objectives
    The prediction model can be refined along with the using and more data was got
  • 18. Thanks!
    18